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Learn Data Science using R from scratch. Build your career as a Data Scientist. Explore knitr, buzz dataset, adv methods
Updated on Sep, 2026
Programming, Data Science, R Programming
Duration - 21.5 hours
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A warm welcome to the Data Science with R course by Uplatz.
Data Science includes various fields such as mathematics, business insight, tools, processes and machine learning techniques. A mix of all these fields help us in discovering the visions or designs from raw data which can be of major use in the formation of big business decisions. As a Data scientist it’s your role to inspect which questions want answering and where to find the related data. A data scientist should have business insight and analytical services. One also needs to have the skill to mine, clean, and present data. Businesses use data scientists to source, manage, and analyze large amounts of unstructured data.
R is a commanding language used extensively for data analysis and statistical calculating. It was developed in early 90s. R is an open-source software. R is unrestricted and flexible because it’s an open-source software. R’s open lines permit it to incorporate with other applications and systems. Open-source soft wares have a high standard of quality, since multiple people use and iterate on them. As a programming language, R delivers objects, operators and functions that allow employers to discover, model and envision data. Data science with R has got a lot of possibilities in the commercial world. Open R is the most widely used open-source language in analytics. From minor to big initiatives, every other company is preferring R over the other languages. There is a constant need for professionals with having knowledge in data science using R programming.
Uplatz provides this comprehensive course on Data Science with R covering data science concepts implementation and application using R programming language.
Data Science with R - Course Syllabus
1. Introduction to Data Science
1.1 The data science process
1.2 Stages of a data science project
1.3 Setting expectations
2. Loading Data into R
2.1 Working with data from files
2.2 Working with relational databases
3.2 Sampling for modeling and validation
4. Choosing and Evaluating Models
4.1 Mapping problems to machine learning tasks
4.2 Evaluating models
4.3 Validating models
5. Memorization Methods
5.1 Using decision trees 127
6. Linear and Logistic Regression
6.1 Using linear regression
6.2 Using logistic regression
7. Unsupervised Methods
7.1 Cluster analysis
7.2 Association rules
8. Exploring Advanced Methods
8.1 Using bagging and random forests to reduce training variance
8.2 Using generalized additive models (GAMs) to learn nonmonotone relationships
8.3 Using kernel methods to increase data separation
8.4 Using SVMs to model complicated decision boundaries
9. Documentation and Deployment
9.1 The buzz dataset
9.2 Using knitr to produce milestone documentation
Learn to program in R at a good level
Learn how to use R Studio
Learn the core principles of programming
Learn how to create vectors in R
Learn how to create variables
Learn about integer, double, logical, character and other types in R
Learn how to create a while() loop and a for() loop in R
Learn how to build and use matrices in R
Learn the matrix() function, learn rbind() and cbind()
Learn how to install packages in R
Learn how to customize R studio to suit your preferences
Understand the Law of Large Numbers
Understand the Normal distribution
Practice working with statistical data in R
Practice working with financial data in R
Practice working with sports data in R
No prior knowledge or experience needed. Only a passion to be successful!
Check out the detailed breakdown of what’s inside the course
Uplatz is a UK-based leading IT Training provider serving students across the globe. Our uniqueness comes from the fact that we provide online training courses at a fraction of the average cost of these courses in the market.
Within a short span of 6 years, Uplatz has grown massively to become a truly global IT training provider with a wide range of career-oriented courses on cutting-edge technologies and software programming.
Our specialization includes Data Science, Machine Learning, Deep Learning, Data Engineering, AWS, SAP, Oracle, Salesforce, Microsoft Azure, GCP, DevOps, SAS, Python, R, JavaScript, Java, C, C++, Full Stack Web Development, Angular, React, NodeJS, Django, IoT, Cybersecurity, BI & Visualization, Tableau, Power BI, Data warehousing, ETL tools, ServiceNow, Software Testing, RPA, Embedded Engineering, Automotive Engineering, DSP, VHDL, Microcontrollers, Electronics, Computer Hardware Engineering, MATLAB, Digital Marketing, Product Marketing, Finance, Accounting, Tally, and more.
Founded in March 2017, Uplatz has seen a phenomenal rise in the training industry providing training on 300+ self-paced courses and 5000+ tutor-led courses across 180 countries having served 1.5 million students in a period of just a few years.
Uplatz's training courses are highly structured, subject-focused, and job-oriented with strong emphasis on practice and assignments. Our courses are designed and taught by highly skilled and experienced instructors who have strong expertise in varied fields whether it be Cloud Computing, SAP, Oracle, Salesforce, Programming Languages, Web Development, or any other technology and in-demand software.
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